We performed a comparison between Databricks and IBM Watson Studio based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Databricks gives us the ability to build a lakehouse framework and do everything implicit to this type of database structure. We also like the ability to stream events. Databricks covers a broad spectrum, from reporting and machine learning to streaming events. It's important for us to have all these features in one platform."
"Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data."
"The setup was straightforward."
"The time travel feature is the solution's most valuable aspect."
"Automation with Databricks is very easy when using the API."
"It's easy to increase performance as required."
"Databricks provides a consistent interface for data engineers to work with data in a consistent language on a single integrated platform for ingesting, processing, and serving data to the end user."
"Ability to work collaboratively without having to worry about the infrastructure."
"It stands out for its substantial AI capabilities, offering a broad spectrum of features for crafting solutions that meet specific requirements."
"The solution is very easy to use."
"Stability-wise, it is a great tool."
"Watson Studio is very stable."
"It is a very stable and reliable solution."
"It is a stable, reliable product."
"The main benefit is the ease of use. We see a lot of engineers in our site and customers that really like the way the tools are able to work with the people."
"The most important thing is that it's a multi-faceted solution. It's a kind of specialist, not a generalist. It can produce very specific information for the customer. It's totally different from Google or any search engine that produces generic information. It's specialty is that it's all on video."
"I believe that this product could be improved by becoming more user-friendly."
"Support for Microsoft technology and the compatibility with the .NET framework is somewhat missing."
"Doesn't provide a lot of credits or trial options."
"The product should incorporate more learning aspects. It needs to have a free trial version that the team can practice."
"The tool should improve its integration with other products."
"The integration features could be more interesting, more involved."
"The solution could be improved by adding a feature that would make it more user-friendly for our team. The feature is simple, but it would be useful. Currently, our team is more familiar with the language R, but Databricks requires the use of Jupyter Notebooks which primarily supports Python. We have tried using RStudio, but it is not a fully integrated solution. To fully utilize Databricks, we have to use the Jupyter interface. One feature that would make it easier for our team to adopt the Jupyter interface would be the ability to select a specific variable or line of code and execute it within a cell. This feature is available in other Jupyter Notebooks outside of Databricks and in our own IDE, but it is not currently available within Databricks. If this feature were added, it would make the transition to using Databricks much smoother for our team."
"The solution has some scalability and integration limitations when consolidating legacy systems."
"More features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier."
"Initially, it was quite complex. For us, it was not only a matter of getting it installed, that was just a start. It was also trying to come up with a standard way of implementing it across the entire organization, which had been a challenge."
"The decision making in their decision making feature is less good than other options."
"I think maybe the support is an area where it lacks."
"We would like to see it less as one big, massive product, but more based on smaller services that we can then roll out to consumers."
"I want IBM's technical support team to provide more specific answers to queries."
"The main challenge lies in visibility and ease of use."
"It's sometimes easy to get lost given the number of images the solution opens up when you click on the mouse and the amount of different tabs."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while IBM Watson Studio is ranked 10th in Data Science Platforms with 13 reviews. Databricks is rated 8.2, while IBM Watson Studio is rated 8.2. The top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". On the other hand, the top reviewer of IBM Watson Studio writes "A highly robust and well-documented platform that simplifies the complex world of AI". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Microsoft Azure Machine Learning Studio and Dremio, whereas IBM Watson Studio is most compared with Azure OpenAI, Microsoft Azure Machine Learning Studio, Google Vertex AI, Amazon Comprehend and Anaconda. See our Databricks vs. IBM Watson Studio report.
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We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
